AIMC Topic: Machine Learning

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Daily motionless activities: A dataset with accelerometer, magnetometer, gyroscope, environment, and GPS data.

Scientific data
The dataset presented in this paper presents a dataset related to three motionless activities, including driving, watching TV, and sleeping. During these activities, the mobile device may be positioned in different locations, including the pants pock...

Integrating deep learning and unbiased automated high-content screening to identify complex disease signatures in human fibroblasts.

Nature communications
Drug discovery for diseases such as Parkinson's disease are impeded by the lack of screenable cellular phenotypes. We present an unbiased phenotypic profiling platform that combines automated cell culture, high-content imaging, Cell Painting, and dee...

A Unified Neural Network Framework for Extended Redundancy Analysis.

Psychometrika
Component-based approaches have been regarded as a tool for dimension reduction to predict outcomes from observed variables in regression applications. Extended redundancy analysis (ERA) is one such component-based approach which reduces predictors t...

A Systematic Review and Bibliometric Analysis of Applications of Artificial Intelligence and Machine Learning in Vascular Surgery.

Annals of vascular surgery
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) have seen increasingly intimate integration with medicine and healthcare in the last 2 decades. The objective of this study was to summarize all current applications of AI and ML in t...

Machine-Learning-Assisted Recognition on Bioinspired Soft Sensor Arrays.

ACS nano
Soft interfaces with self-sensing capabilities play an essential role in environment awareness and reaction. The growing overlap between materials and sensory systems has created a myriad of challenges for sensor integration, including the design of ...

Condition Monitoring of Ball Bearings Based on Machine Learning with Synthetically Generated Data.

Sensors (Basel, Switzerland)
Rolling element bearing faults significantly contribute to overall machine failures, which demand different strategies for condition monitoring and failure detection. Recent advancements in machine learning even further expedite the quest to improve ...

Product Processing Quality Classification Model for Small-Sample and Imbalanced Data Environment.

Computational intelligence and neuroscience
With the rapid development of machine learning technology, how to use machine learning technology to empower the manufacturing industry has become a research hotspot. In order to solve the problem of product quality classification in a small sample d...

A Novel Reformed Reduced Kernel Extreme Learning Machine with RELIEF-F for Classification.

Computational intelligence and neuroscience
With the exponential growth of the Internet population, scientists and researchers face the large-scale data for processing. However, the traditional algorithms, due to their complex computation, are not suitable for the large-scale data, although th...